C++ code
26 papers with code • 0 benchmarks • 0 datasets
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Most implemented papers
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
NVlabs/SegFormer
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NeurIPS 2021
We present SegFormer, a simple, efficient yet powerful semantic segmentation framework which unifies Transformers with lightweight multilayer perception (MLP) decoders.
OpenGM: A C++ Library for Discrete Graphical Models
OpenGM is a C++ template library for defining discrete graphical models and performing inference on these models, using a wide range of state-of-the-art algorithms.
PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments
This paper proposes PL-SLAM, a stereo visual SLAM system that combines both points and line segments to work robustly in a wider variety of scenarios, particularly in those where point features are scarce or not well-distributed in the image.
$μ$NCA: Texture Generation with Ultra-Compact Neural Cellular Automata
google-research/self-organising-systems
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We study the problem of example-based procedural texture synthesis using highly compact models.
FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge
TomG008/SkyNet
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While embedded FPGAs are attractive platforms for DNN acceleration on edge-devices due to their low latency and high energy efficiency, the scarcity of resources of edge-scale FPGA devices also makes it challenging for DNN deployment.
Structural Language Models of Code
tech-srl/slm-code-generation
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ICML 2020
We introduce a new approach to any-code completion that leverages the strict syntax of programming languages to model a code snippet as a tree - structural language modeling (SLM).
Neural Transfer Learning for Repairing Security Vulnerabilities in C Code
To sum up, this paper shows that transfer learning works well for repairing security vulnerabilities in C compared to learning on a small dataset.
The Limits of Mathematics (in C)
This is a shortened version of "The Limits of Mathematics--Course Outline & Software" (IBM Research Report RC 19324, December 1993) in which all Mathematica code has either been deleted or, if absolutely necessary, replaced by C code.
Cross-Language Learning for Program Classification using Bilateral Tree-Based Convolutional Neural Networks
bdqnghi/bi-tbcnn
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It is layered on top of two tree-based convolutional neural networks (TBCNNs), each of which recognizes the algorithm of code written in an individual programming language.
Genetic Algorithm for the 0/1 Multidimensional Knapsack Problem
The 0/1 multidimensional knapsack problem is the 0/1 knapsack problem with m constraints which makes it difficult to solve using traditional methods like dynamic programming or branch and bound algorithms.
