Search Results for author:
Found 10 papers, 8 papers with code
Deep MDP: A Modular Framework for Multi-Object Tracking
This paper presents a fast and modular framework for Multi-Object Tracking (MOT) based on the Markov descision process (MDP) tracking-by-detection paradigm.
Towards Early Prediction of Human iPSC Reprogramming Success
This paper presents advancements in automated early-stage prediction of the success of reprogramming human induced pluripotent stem cells (iPSCs) as a potential source for regenerative cell therapies. The minuscule success rate of iPSC-reprogramming of around $ 0. 01% $ to $ 0. 1% $ makes it labor-intensive, time-consuming, and exorbitantly expensive to generate a stable iPSC line.
To Filter Prune, or to Layer Prune, That Is The Question
LayerPrune presents a set of layer pruning methods based on different criteria that achieve higher latency reduction than filter pruning methods on similar accuracy.
Animal Detection in Man-made Environments
Automatic detection of animals that have strayed into human inhabited areas has important security and road safety applications.
River Ice Segmentation with Deep Learning
This paper deals with the problem of computing surface ice concentration for two different types of ice from digital images of river surface.
Real-Time Salient Closed Boundary Tracking via Line Segments Perceptual Grouping
The tracking scheme is coherently integrated into a perceptual grouping framework in which the visual tracking problem is tackled by identifying a subset of these line segments and connecting them sequentially to form a closed boundary with the largest saliency and a certain similarity to the previous one.
4-DoF Tracking for Robot Fine Manipulation Tasks
One of these trackers is a newly developed learning based tracker that relies on learning discriminative correlation filters while the other is a refinement of a recent 8 DoF RANSAC based tracker adapted with a new appearance model for tracking 4 DoF motion.
Unifying Registration based Tracking: A Case Study with Structural Similarity
This paper adapts a popular image quality measure called structural similarity for high precision registration based tracking while also introducing a simpler and faster variant of the same.
Modular Decomposition and Analysis of Registration based Trackers
We show how existing trackers can be broken down using the suggested methodology and compare the performance of the default configuration chosen by the authors against other possible combinations to demonstrate the new insights that can be gained by such an approach.
Modular Tracking Framework: A Unified Approach to Registration based Tracking
This paper presents a modular, extensible and highly efficient open source framework for registration based tracking called Modular Tracking Framework (MTF).
