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Found 9 papers, 3 papers with code
FuzzyLogic.jl: a Flexible Library for Efficient and Productive Fuzzy Inference
This paper introduces \textsc{FuzzyLogic. jl}, a Julia library to perform fuzzy inference.
Binarized Convolutional Neural Networks for Efficient Inference on GPUs
This representation completely eliminates the need for floating point multiplications and additions and decreases both the computational load and the memory footprint compared to a full-precision network implemented in floating point, making it well-suited for resource-constrained environments.
Can You Trust Your Pose? Confidence Estimation in Visual Localization
Camera pose estimation in large-scale environments is still an open question and, despite recent promising results, it may still fail in some situations.
Sensor Networks TDOA Self-Calibration: 2D Complexity Analysis and Solutions
Given a network of receivers and transmitters, the process of determining their positions from measured pseudoranges is known as network self-calibration.
LightSAL: Lightweight Sign Agnostic Learning for Implicit Surface Representation
Recently, several works have addressed modeling of 3D shapes using deep neural networks to learn implicit surface representations.
Convolutional Neural Network-based Efficient Dense Point Cloud Generation using Unsigned Distance Fields
Dense point cloud generation from a sparse or incomplete point cloud is a crucial and challenging problem in 3D computer vision and computer graphics.
Fault-Tolerant Collaborative Inference through the Edge-PRUNE Framework
Collaborative inference has received significant research interest in machine learning as a vehicle for distributing computation load, reducing latency, as well as addressing privacy preservation in communications.
SADT: Combining Sharpness-Aware Minimization with Self-Distillation for Improved Model Generalization
Methods for improving deep neural network training times and model generalizability consist of various data augmentation, regularization, and optimization approaches, which tend to be sensitive to hyperparameter settings and make reproducibility more challenging.
TBPos: Dataset for Large-Scale Precision Visual Localization
Usually the query images have been acquired with a camera that differs from the imaging hardware used to collect the 3D database; consequently, it is hard to acquire accurate ground truth poses between query images and the 3D database.
