Sabbatical leave report: Spring 2014 - Antonios, Imad (2014)
the page describes the 3 projects Antonios completed: Data Network Traffic Analysis, Gossiping Algorithm Development and Analysis, and ZigBee Networks
Keywords: dept.csc; faculty_collection; sabbatical_report

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation - Girshick, Ross B.; Donahue, Jeff; Darrell, Trevor; Malik, J. (2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014)
Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that typically combine multiple low-level image features with high-level context. In this paper, we propose a simple and scalable detection algorithm that improves mean average precision (mAP) by more than 30% relative to the previous best result on VOC 2012 – achieving a mAP of 53.3%. Our approach combines two key insights: (1) one can apply high-capacity convolutional neural networks (CNNs) to bottom-up region proposals in order to localize and segment objects and (2) when labeled training data is scarce, supervised pre-training for an auxiliary task, followed by domain-specific fine-tuning, yields a significant performance boost. Since we combine region proposals with CNNs, we call our method R-CNN: Regions with CNN features. We also present experiments that provide insight into what the network learns, revealing a rich hierarchy of image features. Source code for the complete system is available at http://www.cs.berkeley.edu/ rbg/rcnn.
14474 citations (Crossref) [2023-10-31]

Google docs, forms and video mashup using HTML5 for assessment applications - Workman, Robert (Society for Information Technology & Teacher Education International Conference, 2014)
Citation Key Alias: lens.org/171-160-143-094-643
Keywords: dept.csc; ⛔ No DOI found