SPANet: Structure-Preserved Attention Activated Network for Weakly Supervised Object Localization.

By exploring the localizable representations in deep CNN, weakly supervised object localization (WSOL) methods could determine the position of the object in each image just trained by the classification task. However, the partial activation problem caused by the discriminant function makes the network unable to locate objects accurately. To alleviate this problem, we propose Structure-Preserved Attention Activated Network (SPA2Net), a simple and effective one-stage WSOL framework to explore the ability of structure preservation of deep features.

TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization.

Weakly supervised object localization (WSOL), which trains object localization models using solely image category annotations, remains a challenging problem. Existing approaches based on convolutional neural networks (CNNs) tend to miss full object extent while activating discriminative object parts. Based on our analysis, this is caused by CNN's intrinsic characteristics, which experiences difficulty to capture object semantics at long distances.

Experimental and comparative study of Chinese commercial improved coal-fired cooking and space-heating stoves.

The extensive use of traditional cooking stoves to meet daily cooking and heating requirements has highlighted the serious problem of indoor and outdoor air pollution. This study evaluates three improved cooking and heating stoves (ICHSs) and compared them with a traditional stove as a baseline reference. The stoves' performance regarding emission and thermal efficiency was evaluated with burning raw coal.

Content-Based Visual Summarization for Image Collections.

With the surge of images in the information era, people demand an effective and accurate way to access meaningful visual information. Accordingly, effective and accurate communication of information has become indispensable. In this article, we propose a content-based approach that automatically generates a clear and informative visual summarization based on design principles and cognitive psychology to represent image collections.