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In this paper, we explore how to leverage readily available unlabeled data to improve semi-supervised human detection performance. For this purpose, we specifically modify the region proposal network (RPN) for learning on a partially labeled dataset. Based on commonly observed false positive types, a verification module is developed to assess foreground human objects in the candidate regions to provide an important cue for filtering the RPN's proposals. The remaining proposals with high confidence scores are then used as pseudo annotations for re-training our detection model. To reduce the risk of error propagation in the training process, we adopt a self-paced training strategy to progressively include more pseudo annotations generated by the previous model over multiple training rounds. The resulting detector re-trained on the augmented data can be expected to have better detection performance. The effectiveness of the main components of this framework is verified through extensive experiments, and the proposed approach achieves state-of-the-art detection results on multiple scene-specific human detection benchmarks in the semi-supervised setting.
This article was published in the following journal.
Name: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
A protein complex is a group of associated polypeptide chains which plays essential roles in the biological process. Given a graph representing protein-protein interactions (PPI) network, it is critic...
The advent of deep learning has pushed medical image analysis to new levels, rapidly replacing more traditional machine learning and computer vision pipelines. However segmenting and labelling anatomi...
In this paper, we propose a distributed semi-supervised learning (DSSL) algorithm based on the extreme learning machine (ELM) algorithm over communication network using the event-triggered (ET) commun...
Classification of benign-malignant lung nodules on chest CT is the most critical step in the early detection of lung cancer and prolongation of patient survival. Despite their success in image classif...
Brain image segmentation is of great importance not only for clinical use but also for neuroscience research. Recent developments in deep neural networks (DNNs) have led to the application of DNNs to ...
The purpose of this project is to examine the role of machine learning and computer aided diagnostics in automatic polyp detection and to determine in real-time how a computer-aided detect...
The purpose of this study is to compare computer aided design/computer aided manufacturing (CAD/CAM) and semi-custom insole types on pain, quality of life and physical performance and also...
We aim to experiment and implement various deep learning architectures in order to achieve human-level accuracy in Computer-aided diagnosis (CAD) systems. In particular, we are interested ...
RATIONALE: A computer-aided detection program may help doctors find breast cancer sooner, when it may be easier to treat, in women undergoing screening mammography. PURPOSE: This randomiz...
We developed an artificial intelligent computer system with a deep neural network to analyze real-time video signals from the endoscopy station. This randomised controlled trial compared a...
Detection of drugs that have been abused, overused, or misused, including legal and illegal drugs. Urine screening is the usual method of detection.
Antibodies from non-human species whose protein sequences have been modified to make them nearly identical with human antibodies. If the constant region and part of the variable region are replaced, they are called humanized. If only the constant region is modified they are called chimeric. INN names for humanized antibodies end in -zumab.
A regulatory region first identified in the human beta-globin locus but subsequently found in other loci. The region is believed to regulate GENETIC TRANSCRIPTION by opening and remodeling CHROMATIN structure. It may also have enhancer activity.
Hemagglutination test in which Coombs' reagent (antiglobulin, or anti-human globulin rabbit immune serum) is added to detect incomplete (non-agglutinating, univalent, blocking) antibodies coating erythrocytes. The direct test is applied to red cells which have been coated with antibody in vivo (e.g., in hemolytic disease of newborn, autoimmune hemolytic anemia, and transfusion reactions). The indirect test is applied to serum to detect the presence of antibody (e.g., in detection of incompatibility in cross-matching tests, detection and identification of irregular antibodies, and in detection of antibodies not identifiable by other means).
The region corresponding to the human WRIST in non-human ANIMALS.
Standard antiretroviral therapy (ART) consists of the combination of at least three antiretroviral (ARV) drugs to maximally suppress the HIV virus and stop the progression of HIV disease. Huge reductions have been seen in rates of death and suffering whe...