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Articles 5701 - 5730 of 9024
Full-Text Articles in Computer Sciences
A Comparison Of Fundamental Network Formation Principles Between Offline And Online Friends On Twitter, Felicia Natali, Feida Zhu
A Comparison Of Fundamental Network Formation Principles Between Offline And Online Friends On Twitter, Felicia Natali, Feida Zhu
Research Collection School Of Computing and Information Systems
We investigate the differences between how some of the fundamental principles of network formation apply among offline friends and how they apply among online friends on Twitter. We consider three fundamental principles of network formation proposed by Schaefer et al.: reciprocity, popularity, and triadic closure. Overall, we discover that these principles mainly apply to offline friends on Twitter. Based on how these principles apply to offline versus online friends, we formulate rules to predict offline friendship on Twitter. We compare our algorithm with popular machine learning algorithms and Xiewei’s random walk algorithm. Our algorithm beats the machine learning algorithms on …
Information Source Detection Via Maximum A Posteriori Estimation, Biao Chang, Feida Zhu, Enhong Chen, Qi. Liu
Information Source Detection Via Maximum A Posteriori Estimation, Biao Chang, Feida Zhu, Enhong Chen, Qi. Liu
Research Collection School Of Computing and Information Systems
The problem of information source detection, whose goal is to identify the source of a piece of information from a diffusion process (e.g., computer virus, rumor, epidemic, and so on), has attracted ever-increasing attention from research community in recent years. Although various methods have been proposed, such as those based on centrality, spectral and belief propagation, the existing solutions still suffer from high time complexity and inadequate effectiveness. To this end, we revisit this problem in the paper and present a comprehensive study from the perspective of likelihood approximation. Different from many previous works, we consider both infected and uninfected …
Demo: Profiling Power Utilization Behaviours Of Smartwatch Applications, Joseph Joo Keng Chan, Lingxiao Jiang, Rajesh Krishna Balan, Youngki Lee, Archan Misra
Demo: Profiling Power Utilization Behaviours Of Smartwatch Applications, Joseph Joo Keng Chan, Lingxiao Jiang, Rajesh Krishna Balan, Youngki Lee, Archan Misra
Research Collection School Of Computing and Information Systems
Smartwatches complement the main mobile phone and are able to profile user-activity as well as provide links, updates and notifications with work or personal utilities (e.g. Email, Social Media, Messaging etc.). Although very promising, smartwatches are still limited by low battery life. This is due to the small size of the battery as well as the need to continuously perform sensing. Battery drain issues by apps as well as the system are a common complaint by users. Improved tools for power analysis and profiling of smartwatch apps can help both developers (by providing a platform for pre-release analysis) and users …
Demo: Real-World Deployment Of Seat Occupancy Detectors, Nguyen Huy Hoang Nguyen, Gihan Hettiarachchi, Youngki Lee, Rajesh Krishna Balan
Demo: Real-World Deployment Of Seat Occupancy Detectors, Nguyen Huy Hoang Nguyen, Gihan Hettiarachchi, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Detecting occupancy of seats in library is important for librarians to check seats’ usage, and for students to find available seats in crowded time. In our prior work [1], we presented in-lab micro benchmarks to show feasibility of capacitive sensing for seat occupancy detection. In this demo paper, we present larger scale real-world deployment of occupancy detection system and its performance.
Demo: Sensing Gamers' Emotions Using Physiological Sensors, Sinh Huynh, Rajesh Krishna Balan, Youngki Lee
Demo: Sensing Gamers' Emotions Using Physiological Sensors, Sinh Huynh, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Understanding emotions of gamers can benefit game designers in various ways. How gamers feel while they playing a game can be treated as valuable user feedback to improve the development process of that game. Sensing player emotions also enables game designers to create adaptive game that can adjust itself to provide best gaming experience based on player emotions. However, how to effectively evaluate emotions of gamers is still an open research challenge. Two common techniques to evaluate emotional state are using self-assessments such as questionnaires or interviews, and to recognize expressed emotions by analyzing videos or images of facial expression, …
Demo: Smartwatch Based Food Diary And Eating Analytics, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Demo: Smartwatch Based Food Diary And Eating Analytics, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Monitoring an individual’s daily dietary intake can provide various insights regarding the health of the individual. Applications such as My Fitness Pal exists, which allows individuals to monitor all items that the individual consumed. However, manual monitoring can be labour intensive. To overcome this limitation, wrist worn sensor based eating habit monitoring has been studied by various researchers. These systems can detect eating gesture, but they cannot determine what is being eaten. We have built a system which can (i) detect eating gesture using the smartwatch's inertial sensors (ii) use the smartwatch's camera to capture images of food consumed at …
Demo: Sound Localization Using Smartphone, Amit Sharma, Youngki Lee
Demo: Sound Localization Using Smartphone, Amit Sharma, Youngki Lee
Research Collection School Of Computing and Information Systems
Smartphones based sound direction estimation can be helpful in many situations. For example, a deaf person in a meeting room can look at the smartphone to find out which direction the speaker is in and then he can look in appropriate direction to read lips/gestures of the speaker. Many smartphones today come with two built-in microphones located at physically different positions. This difference in position can cause time difference of arrival (TDOA) of sound on both microphones. Value of TDOA for two microphones may vary depending on the location of sound source with respect to the smartphone. This time difference …
Demo: Towards Immersive And Interactive Gym Exercises, Fazlay Rabbi, Taiwoo Park, Biyi Fang, Mi Zhang, Youngki Lee, Rajiv Ranganathan
Demo: Towards Immersive And Interactive Gym Exercises, Fazlay Rabbi, Taiwoo Park, Biyi Fang, Mi Zhang, Youngki Lee, Rajiv Ranganathan
Research Collection School Of Computing and Information Systems
We demonstrate JARVIS, a novel virtual coaching system based on virtual reality (VR) and Internet of Things (IoT) technologies. It creates a truly immersive gym exercising experience for machine-based strength training and guides users in a highly interactive manner. With these unique advantages, we believe that JARVIS has a potential to revolutionize personal fitness experiences.
Friendship Maintenance And Prediction In Multiple Social Networks, Roy Ka-Wei Lee, Ee-Peng Lim
Friendship Maintenance And Prediction In Multiple Social Networks, Roy Ka-Wei Lee, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendships and interact with other users in these OSNs. In this work, we analyze how users maintain friendship in multiple OSNs by studying users who have accounts in both Twitter and Instagram. Specifically, we study the similarity of a user's friendship and the evenness of friendship distribution in multiple OSNs. Our study shows that most users in Twitter and Instagram prefer to maintain different friendships in the two OSNs, keeping only a small clique of …
Powerforecaster: Predicting Power Impact Of Mobile Sensing Applications At Pre-Installation Time, Chulhong Min, Youngki Lee, Chungkuk Yoo, Seungwoo Kang, Inseok Hwang, Junehwa Song
Powerforecaster: Predicting Power Impact Of Mobile Sensing Applications At Pre-Installation Time, Chulhong Min, Youngki Lee, Chungkuk Yoo, Seungwoo Kang, Inseok Hwang, Junehwa Song
Research Collection School Of Computing and Information Systems
Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe …
Performance Based Contracting For The Manufacturing Industry By Using Integrated Platform And Dynamic Pricing Model, Lindawati, Aldy Gunawan
Performance Based Contracting For The Manufacturing Industry By Using Integrated Platform And Dynamic Pricing Model, Lindawati, Aldy Gunawan
Research Collection Lee Kong Chian School Of Business
Although Performance Based Contracting (PBC) concept is not totally new, the PBC adaptation in Industrial Machinery and Components (IMC) manufacturing, which produces high-value and long life machineries, is rather slow and it is done with extra caution. Three main concerns for manufacturers to implement PBC are the investment cost, the maintenance cost and possible revenue loss. To handle these concerns and accelerate the PBC implementation, we propose an integrated platform that consists of three components: dynamic pricing, sensor data feeding and machinery monitoring. We model the dynamic pricing as an optimization problem and propose Genetic Algorithm to solve the problem. …
All Your Sessions Are Belong To Us: Investigating Authenticator Leakage Through Backup Channels On Android, Guangdong Bai, Jun Sun, Jianliang Wu, Quanqi Ye, Li Li, Jin Song Dong, Shanqing Guo
All Your Sessions Are Belong To Us: Investigating Authenticator Leakage Through Backup Channels On Android, Guangdong Bai, Jun Sun, Jianliang Wu, Quanqi Ye, Li Li, Jin Song Dong, Shanqing Guo
Research Collection School Of Computing and Information Systems
Security of authentication protocols heavily relies on the confidentiality of credentials (or authenticators) like passwords and session IDs. However, unlike browser-based web applications for which highly evolved browsers manage the authenticators, Android apps have to construct their own management. We find that most apps simply locate their authenticators into the persistent storage and entrust underlying Android OS for mediation. Consequently, these authenticators can be leaked through compromised backup channels. In this work, we conduct the first systematic investigation on this previously overlooked attack vector. We find that nearly all backup apps on Google Play inadvertently expose backup data to any …
Gpu Accelerated On-The-Fly Reachability Checking, Zhimin Wu, Yang Liu, Jun Sun, Jianqi Shi, Shengchao Qin
Gpu Accelerated On-The-Fly Reachability Checking, Zhimin Wu, Yang Liu, Jun Sun, Jianqi Shi, Shengchao Qin
Research Collection School Of Computing and Information Systems
Model checking suffers from the infamous state space explosion problem. In this paper, we propose an approach, named GPURC, to utilize the Graphics Processing Units (GPUs) to speed up the reachability verification. The key idea is to achieve a dynamic load balancing so that the many cores in GPUs are fully utilized during the state space exploration.To this end, we firstly construct a compact data encoding of the input transition systems to reduce the memory cost and fit the calculation in GPUs. To support a large number of concurrent components, we propose a multi-integer encoding with conflict-release accessing approach. We …
Learning Query And Image Similarities With Ranking Canonical Correlation Analysis, Ting Yao, Tao Mei, Chong-Wah Ngo
Learning Query And Image Similarities With Ranking Canonical Correlation Analysis, Ting Yao, Tao Mei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
One of the fundamental problems in image search is to learn the ranking functions, i.e., similarity between the query and image. The research on this topic has evolved through two paradigms: feature-based vector model and image ranker learning. The former relies on the image surrounding texts, while the latter learns a ranker based on human labeled query-image pairs. Each of the paradigms has its own limitation. The vector model is sensitive to the quality of text descriptions, and the learning paradigm is difficult to be scaled up as human labeling is always too expensive to obtain. We demonstrate in this …
Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan
Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Ageing in place demands a new paradigm of inhouse caregiving allowing many aspects of daily lives to be tackled by smart appliances and technologies. The important challenges include the effective provision of recommendations by multiple parties of caregiver constituting changes of the user's behavior. In this multiagent environment, interdependencies between agents become major issues to tackle. This paper presents an approach of dynamic group formation for autonomous caregiving agents to collaborate in recommending different aspects of well-being. The approach supports the agents to regulate the timing of their recommendations, prevent conflicting messages, and cooperate to make more effective persuasions. A …
Fast Reinforcement Learning Under Uncertainties With Self-Organizing Neural Networks, Teck-Hou Teng, Ah-Hwee Tan
Fast Reinforcement Learning Under Uncertainties With Self-Organizing Neural Networks, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Using feedback signals from the environment, a reinforcement learning (RL) system typically discovers action policies that recommend actions effective to the states based on a Q-value function. However, uncertainties over the estimation of the Q-values can delay the convergence of RL. For fast RL convergence by accounting for such uncertainties, this paper proposes several enhancements to the estimation and learning of the Q-value using a self-organizing neural network. Specifically, a temporal difference method known as Q-learning is complemented by a Q-value Polarization procedure, which contrasts the Q-values using feedback signals on the effect of the recommended actions. The polarized Q-values …
Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan
Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Ageing in place demands a new paradigm of inhouse caregiving allowing many aspects of daily lives to be tackled by smart appliances and technologies. The important challenges include the effective provision of recommendations by multiple parties of caregiver constituting changes of the user’s behavior. In this multiagent environment, interdependencies between agents become major issues to tackle. This paper presents an approach of dynamic group formation for autonomous caregiving agents to collaborate in recommending different aspects of well-being. The approach supports the agents to regulate the timing of their recommendations, prevent conflicting messages, and cooperate to make more effective persuasions. A …
A Benchmark And Comparative Study Of Video-Based Face Recognition On Cox Face Database, Zhiwu Huang, S. Shan, R. Wang, H. Zhang, S. Lao, A. Kuerban, X. Chen
A Benchmark And Comparative Study Of Video-Based Face Recognition On Cox Face Database, Zhiwu Huang, S. Shan, R. Wang, H. Zhang, S. Lao, A. Kuerban, X. Chen
Research Collection School Of Computing and Information Systems
Face recognition with still face images has been widely studied, while the research on video-based face recognition is inadequate relatively, especially in terms of benchmark datasets and comparisons. Real-world video-based face recognition applications require techniques for three distinct scenarios: 1) Videoto-Still (V2S); 2) Still-to-Video (S2V); and 3) Video-to-Video (V2V), respectively, taking video or still image as query or target. To the best of our knowledge, few datasets and evaluation protocols have benchmarked for all the three scenarios. In order to facilitate the study of this specific topic, this paper contributes a benchmarking and comparative study based on a newly collected …
Lossy Projective Hashing And Its Applications, Haiyang Xue, Yamin Liu, Xianhui Lu, Bao Li
Lossy Projective Hashing And Its Applications, Haiyang Xue, Yamin Liu, Xianhui Lu, Bao Li
Research Collection School Of Computing and Information Systems
In this paper, we introduce a primitive called lossy projective hashing. It is unknown before whether smooth projective hashing (Cramer-Shoup, Eurocrypt’02) can be constructed from dual projective hashing (Wee, Eurocrypt’12). The lossy projective hashing builds a bridge between dual projective hashing and smooth projective hashing. We give instantiations of lossy projective hashing from DDH, DCR, QR and general subgroup membership assumptions (including 2k-th residue, p-subgroup and higher residue assumptions). We also show how to construct lossy encryption and fully IND secure deterministic public key encryption from lossy projective hashing. – We give a construction of lossy projective hashing via dual …
Adaptive Scaling Of Cluster Boundaries For Large-Scale Social Media Data Clustering, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Adaptive Scaling Of Cluster Boundaries For Large-Scale Social Media Data Clustering, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Research Collection School Of Computing and Information Systems
The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the …
A Misspecification Test For Logit Based Route Choice Models, Tien Mai, Emma Frejinger, Fabian Bastin
A Misspecification Test For Logit Based Route Choice Models, Tien Mai, Emma Frejinger, Fabian Bastin
Research Collection School Of Computing and Information Systems
The multinomial logit (MNL) model is often used for analyzing route choices in real networks in spite of the fact that path utilities are believed to be correlated. Yet, statistical tests for model misspecification are rarely used. This paper shows how the information matrix test for model misspecification proposed byWhite (1982) can be applied to test path-based and link-based MNL route choice models.We present a Monte Carlo experiment using simulated data to assess the size and the power of the test and to compare its performance with the IIA (Hausman and McFadden, 1984) and McFadden–Train Lagrange multiplier (McFadden and Train, …
Mylife: An Online Personal Memory Album, Di Wang, Ah-Hwee Tan
Mylife: An Online Personal Memory Album, Di Wang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
In this demo, we illustrate the formation, retrieval, and playback of autobiographical memory in an online personal memory album named MyLife. The memory in MyLife consists of pictorial snapshots of one's life together with the associated context, namely time, location, people, activity, imagery, and emotion. MyLife allows direct import of memories from other online personal photo repositories. For memory retrieval, users can use not only exact cues, but also partial, vague, inaccurate, and random ones. The retrieved memories are then played back as a movie-like slide show with various visual effects and background music. MyLife holds high potential in both …
Preface: Wi 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, Jie Zhang, Dell Zhang, Julita Vassileva
Preface: Wi 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, Jie Zhang, Dell Zhang, Julita Vassileva
Research Collection School Of Computing and Information Systems
This volume contains the papers selected for presentation at the 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI’15), which was held from 6 to 9 December 2015 in Singapore, a city which welcomes people from different parts of the world to work and play. Following the tradition of WI conference in previous years, WI’15 was collocated with 2015 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’15). Both WI’15 and IAT’15 were sponsored by the IEEE Computer Society, Web Intelligence Consortium (WIC), Association for Computing Machinery (ACM), and the Memetic Computing Society. The two collocated conferences were hosted by the Joint …
Preface Iat 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, An Bo, Anita Raja, Sarvapali Ramchurn
Preface Iat 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, An Bo, Anita Raja, Sarvapali Ramchurn
Research Collection School Of Computing and Information Systems
This volume contains the papers selected for presentation at the 2015 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’15), which was held from 6 to 9 December 2015 in Singapore, a city which welcomes people from different parts of the world to work and play. Following the tradition of IAT conference in previous years, IAT’15 was collocated with 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI’15). Both WI’15 and IAT’15 were sponsored by the IEEE Computer Society, Web Intelligence Consortium (WIC), Association for Computing Machinery (ACM), and the Memetic Computing Society. The two collocated conferences were hosted by the Joint …
Preface To Wi-Iat 2015 Workshops And Demo/Posters, Ah-Hwee Tan, Yuefeng Li
Preface To Wi-Iat 2015 Workshops And Demo/Posters, Ah-Hwee Tan, Yuefeng Li
Research Collection School Of Computing and Information Systems
This volume contains the papers selected for presentation at the workshops and demonstration/poster track as part of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI’15) and 2015 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’15) held from 6 to 9 December 2015 in Singapore.
Progressive Sequence Matching For Adl Plan Recommendation, Shan Gao, Di Wang, Ah-Hwee Tan, Chunyan Miao
Progressive Sequence Matching For Adl Plan Recommendation, Shan Gao, Di Wang, Ah-Hwee Tan, Chunyan Miao
Research Collection School Of Computing and Information Systems
Activities of Daily Living (ADLs) are indicatives of a person’s lifestyle. In particular, daily ADL routines closely relate to a person’s well-being. With the objective of promoting active lifestyles, this paper presents an agent system that provides recommendations of suitable ADL plans (i.e., selected ADL sequences) to individual users based on the more active lifestyles of the others. Specifically, we develop a set of quantitative measures, named wellness scores, spanning the evaluation across the physical, cognitive, emotion, and social aspects based on his or her ADL routines. Then we propose an ADL sequence learning model, named Recommendation ADL ART, or …
Silver Assistants For Aging-In-Place, Di Wang, Budhitama Subagdja, Yilin Kang, Ah-Hwee Tan
Silver Assistants For Aging-In-Place, Di Wang, Budhitama Subagdja, Yilin Kang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
In this demo, we present an assembly of silver assistants for supporting Aging-In-Place (AIP). The virtual agents are designed to serve around the clock to complement human care within the intelligent home environment. Residing in different platforms with ubiquitous access, the agents collaboratively provide holistic care to the elderly users. The demonstration is shown in a 3-D virtual home replicating a typical 5-room apartment in Singapore. Sensory inputs are stored in a knowledge base named Situation Awareness Model (SAM). Therefore, the capabilities of the agents can always be extended by expanding the knowledge defined in SAM. Using the simulation system, …
Non-Intrusive Robust Human Activity Recognition For Diverse Age Groups, Di Wang, Ah-Hwee Tan, Daqing Zhang
Non-Intrusive Robust Human Activity Recognition For Diverse Age Groups, Di Wang, Ah-Hwee Tan, Daqing Zhang
Research Collection School Of Computing and Information Systems
—Many elderly prefer to live independently at their own homes. However, how to use modern technologies to ensure their safety presents vast challenges and opportunities. Being able to non-intrusively sense the activities performed by the elderly definitely has great advantages in various circumstances. Non-intrusive activity recognition can be performed using the embedded sensors in modern smartphones. However, not many activity recognition models are robust enough that allow the subjects to carry the smartphones in different pockets with unrestricted orientations and varying deviations. Moreover, to the best of our knowledge, no existing literature studied the difference between the youth and the …
Bl-Mle: Block-Level Message-Locked Encryption For Secure Large File Deduplication, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo
Bl-Mle: Block-Level Message-Locked Encryption For Secure Large File Deduplication, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo
Research Collection School Of Computing and Information Systems
Deduplication is a popular technique widely used to save storage spaces in the cloud. To achieve secure deduplication of encrypted files, Bellare et al. formalized a new cryptographic primitive named message-locked encryption (MLE) in Eurocrypt 2013. Although an MLE scheme can be extended to obtain secure deduplication for large files, it requires a lot of metadata maintained by the end user and the cloud server. In this paper, we propose a new approach to achieve more efficient deduplication for (encrypted) large files. Our approach, named block-level message-locked encryption (BL-MLE), can achieve file-level and block-level deduplication, block key management, and proof …
Supercnn: A Superpixelwise Convolutional Neural Network For Salient Object Detection, Shengfeng He, Rynson W.H. Lau, Wenxi Liu, Zhe Huang, Qingxiong Yang
Supercnn: A Superpixelwise Convolutional Neural Network For Salient Object Detection, Shengfeng He, Rynson W.H. Lau, Wenxi Liu, Zhe Huang, Qingxiong Yang
Research Collection School Of Computing and Information Systems
Existing computational models for salient object detection primarily rely on hand-crafted features, which are only able to capture low-level contrast information. In this paper, we learn the hierarchical contrast features by formulating salient object detection as a binary labeling problem using deep learning techniques. A novel superpixelwise convolutional neural network approach, called SuperCNN, is proposed to learn the internal representations of saliency in an efficient manner. In contrast to the classical convolutional networks, SuperCNN has four main properties. First, the proposed method is able to learn the hierarchical contrast features, as it is fed by two meaningful superpixel sequences, which …