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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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- Learning Spatial-Aware Regressions for Visual Tracking221
This paper proposes a kernelized ridge regression model wherein the kernel value is defined as the weighted sum of similarity scores of all pairs of patches between two samples, and shows that this model can be formulated as a neural network and thus can be efficiently solved.
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- Kernelized Subspace Ranking for Saliency Detection84
A novel saliency method that takes advantage of object-level proposals and region-based convolutional neural network (R-CNN) features and a new kernelized subspace ranking model is proposed by jointly learning a Rank-SVM classifier and a subspace projection.
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- The application of agglomerative hierarchical spatial clustering algorithm in tea blending16
This study enable tea blending to get rid of human experience, instead of intelligent approach and present an agglomerative hierarchical spatial clustering based algorithm to work out the optimal blending program.
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- V-Oracle: Making Progressive Reasoning in Deciphering Oracle Bones for You and Me11
V-Oracle is proposed, an innovative framework that utilizes Large Multi-modal Models (LMMs) for interpreting OBS and applies principles of pictographic character formation and frames the task as a visual question-answering (VQA) problem, establishing a multi-step reasoning chain.
- Gallery: A Machine Learning Model Management System at Uber11
Gallery is described, a machine learning model lifecycle management system to save and serve models and metrics and automatically orchestrate the of models across stages in the lifecycle.
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- An earthquake prediction model based on precursor window detection3
An earthquake prediction method based on time precursory window is proposed in this paper, which is based on the low-frequency electromagnetic signals collected by AETA, and has a good prediction effect.
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Publication data from OpenAlex; 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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