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- The Visual Object Tracking VOT2016 Challenge Results776
The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
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- Ternary Weight Networks604
Extensive experiments show that the TWNs achieve much better result than the Binary-Weight-Networks (BWNs) and the classification performance on MNIST and CIFAR-10 is very close to the full precision networks.
- Cross-Modality Person Re-Identification With Shared-Specific Feature Transfer418
This paper proposes a novel cross-modality shared-specific feature transfer algorithm (termed cm-SSFT) to explore the potential of both the modality-shared information and themodality-specific characteristics to boost the reidentification performance.
- MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small-Target Detection227
Inspired by the recent basic model with linear complexity for long-distance modeling, Mamba, the potential of this state-space model (SSM) for ISTD tasks in terms of effectiveness and efficiency is explored.
- Demo225
This paper designs and implements Medusa, a novel programming framework for crowd-sensing that provides high-level abstractions for specifying the steps required to complete a crowd-Sensing task, and employs a distributed runtime system that coordinates the execution of these tasks between smartphones and a cluster on the cloud.
- Semantics Disentangling for Text-To-Image Generation210
A novel photo-realistic text-to-image generation model that implicitly disentangles semantics to both fulfill the high- level semantic consistency and low-level semantic diversity and a visual-semantic embedding strategy by semantic-conditioned batch normalization to find diverse low- level semantics.
- Fabrication of a pH-Responsively Controlled-Release Pesticide Using an Attapulgite-Based Hydrogel179
The PA-CA hydrogel possessed a benign biocompatibility on Escherichia coli and foxtail millet, showing a high biosafety, and provides a promising approach to pH-responsively controlled release chlorpyrifos.
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- Online multi-object tracking with unsupervised re-identification learning and occlusion estimation111
This study shows that, when applied to state-of-the-art MOT methods, the proposed unsupervised re-Identification learning is comparable to supervised re-identification learning, and the tracking performance is further improved by the proposed occlusion estimation module.
- AResU-Net: Attention Residual U-Net for Brain Tumor Segmentation101
An end-to-end 2D brain tumor segmentation network, i.e., attention residual U- net (AResU-Net), which simultaneously embeds attention mechanism and residual units into U-Net for the further performance improvement of brain tumor segmentsation.
- Joint Color-irrelevant Consistency Learning and Identity-aware Modality Adaptation for Visible-infrared Cross Modality Person Re-identification98
This work proposes a novel approach to VI-ReID that learns the color-irrelevant features through the CICL and aligns the identity-level feature distributions by the Identity-aware modality adaptation (IAMA), which is integrated into a joint learning framework and can promote each other.
- Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN97
The proposed end-to-end fully automatic model which is computationally efficient has the potential to achieve the real automatic diagnosis of knee OA and be used as computer-aided diagnosis tools in clinical applications.
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- Context and Attribute Grounded Dense Captioning83
This work designs a novel end-to-end context and attribute grounded dense captioning framework consisting of a contextual visual mining module and a multi-level attribute grounded description generation module that incorporates an auxiliary supervision from hierarchical linguistic attributes to augment the distinctiveness of the learned captions.
- Breast cancer histopathological image classification using attention high‐order deep network80
A novel attention high‐order deep network (AHoNet) is introduced by simultaneously embedding attention mechanism and high-order statistical representation into a residual convolutional network to capture more discriminant deep features for breast cancer pathological images.
- Infrared-Light-Responsive Controlled-Release Pesticide Using Hollow Carbon Microspheres@Polyethylene Glycol/α-Cyclodextrin Gel70
An infrared-light-responsive pesticide delivery system for the controlled release of imidacloprid by preparation of functional hollow carbon microspheres by providing a promising method to intentionally regulate pesticide release and enhance utilization efficiency.
- Obstacle detection of rail transit based on deep learning66
The Improved-YOLOv4 network based on deep learning obtained the mAP of 93% on NVIDIA Jetson AGX, which is more suitable for the obstacle detection of rail transit.
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- Approximate Nearest Neighbor Search under Neural Similarity Metric for Large-Scale Recommendation58
This paper proposes a novel method to extend ANN search to arbitrary matching functions, e.g., a deep neural network, and proposes a pluggable adversarial training task to ensure the graph search with arbitrary matching function can achieve fairly high precision.
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- Lightweight and Secure Three-Factor Authentication Scheme for Remote Patient Monitoring Using On-Body Wireless Networks53
The proposed lightweight and secure three-factor authentication scheme for remote patient monitoring using oBWNs adopts one-time hash chain technique to ensure forward secrecy, and the pseudonym identity method is employed to provide user anonymity and resist against desynchronization attack.
- Real-Time Online Multi-Object Tracking in Compressed Domain52
This work divides the frames into key and non-key frames and track objects in the compressed domain and proposes an appearance convolutional neural network which can be jointly trained with the detector to make data association more reliable.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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