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Showing Items 1-20 of 27 on page 1 of 2: 1 2 Next

Logo Databases for DMNS source codes 1.0

by openpr_nlpr - May 15, 2018, 07:56:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2359 views, 473 downloads, 0 subscriptions

About: In DMNS source, five databases are used in slover.cpp and data_veh_layer.cpp, these images and databases are included in this file, except munich database.

Changes:

Initial Announcement on mloss.org.


Logo Source codes of DMNS based on caffe platform 1.0

by openpr_nlpr - May 15, 2018, 07:52:48 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2435 views, 466 downloads, 0 subscriptions

About: Deep measuring net sequence(DMNS) is a sequence of three deep measuring nets, the later are deep fcn-based networks, directely output object category score, object orientation, location and scale simultaneously without any anchor boxes. DMNS acheived high accuracy in maneuvering target detection and geometrical measurements. Its average orientation error is less than 3.5 degree, loaction error less than 1.3 pixel, scale measuring error less than 10%, achieve a detection F1-score 96.5% in OAD, 91.8% in SVDS ,90.8% in Munich , 87.3% in OIRDS, outperforms SSD, Fater R-CNN, etc.

Changes:

Initial Announcement on mloss.org.


Logo BOLeRo 1.0.0

by afabisch - February 11, 2018, 19:44:41 CET [ Project Homepage BibTeX Download ] 3572 views, 1119 downloads, 0 subscriptions

About: Behavior Optimization and Learning for Robots

Changes:

https://github.com/rock-learning/bolero/releases/tag/v1.0.0


Logo Aboleth 0.7

by dsteinberg - December 14, 2017, 02:39:19 CET [ Project Homepage BibTeX Download ] 5272 views, 1481 downloads, 0 subscriptions

About: A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Changes:

Release 0.7.0

  • Update to TensorFlow r1.4.

  • Tutorials in the documentation on:

  • Interfacing with Keras

  • Saving/loading models

  • How to build a variety of regressors with Aboleth

  • New prediction module with some convenience functions, including freezing the weight samples during prediction.

  • Bayesian convolutional layers with accompanying demo.

  • Allow the number of samples drawn from a model to be varied by using placeholders.

  • Generalise the feature embedding layers to work on matrix inputs (instead of just column vectors).

  • Numerous numerical and usability fixes.


Logo glyph 0.3.2

by mquade - June 1, 2017, 20:51:52 CET [ Project Homepage BibTeX Download ] 2379 views, 662 downloads, 0 subscriptions

About: glyph is a python 3 library based on deap providing abstraction layers for symbolic regression problems.

Changes:

Initial Announcement on mloss.org.


Logo Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition 1.0

by openpr_nlpr - December 30, 2016, 04:10:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3193 views, 546 downloads, 0 subscriptions

About: Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition

Changes:

Initial Announcement on mloss.org.


Logo QMiner 5.0.0

by blazfortuna - April 8, 2016, 14:17:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7203 views, 1364 downloads, 0 subscriptions

About: Analytic engine for real-time large-scale streams containing structured and unstructured data.

Changes:

Initial Announcement on mloss.org.


Logo efficient psd constrained asymmetric metric learning for person reidentification 1.0

by openpr_nlpr - December 8, 2015, 03:12:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4155 views, 762 downloads, 0 subscriptions

About: This MATLAB package provides the MLAPG algorithm proposed in our ICCV 2015 paper. It is efficient for PSD constrained metric learning, and also effective for person re-identification. For more details, please visit http://www.cbsr.ia.ac.cn/users/scliao/projects/mlapg/.

Changes:

Initial Announcement on mloss.org.


Logo Deep Semantic Ranking Based Hashing 1.0

by openpr_nlpr - November 18, 2015, 07:25:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3924 views, 702 downloads, 0 subscriptions

About: This algorithm is described in Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval. See https://github.com/zhaofang0627/cuda-convnet-for-hashing

Changes:

Initial Announcement on mloss.org.


Logo apsis 0.1.1

by fdiehl - March 17, 2015, 08:27:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4857 views, 1013 downloads, 0 subscriptions

About: A toolkit for hyperparameter optimization for machine learning algorithms.

Changes:

Initial Announcement on mloss.org.


Logo Hivemall 0.3

by myui - March 13, 2015, 17:08:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 17682 views, 3190 downloads, 0 subscriptions

About: Hivemall is a scalable machine learning library running on Hive/Hadoop.

Changes:
  • Supported Matrix Factorization
  • Added a support for TF-IDF computation
  • Supported AdaGrad/AdaDelta
  • Supported AdaGradRDA classification
  • Added normalization scheme

Logo libcmaes 0.9.5

by beniz - March 9, 2015, 09:05:22 CET [ Project Homepage BibTeX Download ] 19497 views, 3951 downloads, 0 subscriptions

About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly non-linear and non-convex functions, using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability.

Changes:

This is a major release, with several novelties, improvements and fixes, among which:

  • step-size two-point adaptaion scheme for improved performances in some settings, ref #88

  • important bug fixes to the ACM surrogate scheme, ref #57, #106

  • simple high-level workflow under Python, ref #116

  • improved performances in high dimensions, ref #97

  • improved profile likelihood and contour computations, including under geno/pheno transforms, ref #30, #31, #48

  • elitist mechanism for forcing best solutions during evolution, ref 103

  • new legacy plotting function, ref #110

  • optional initial function value, ref #100

  • improved C++ API, ref #89

  • Python bindings support with Anaconda, ref #111

  • configure script now tries to detect numpy when building Python bindings, ref #113

  • Python bindings now have embedded documentation, ref #114

  • support for Travis continuous integration, ref #122

  • lower resolution random seed initialization


Logo CN24 Convolutional Neural Networks for Semantic Segmentation 1.0

by erik - February 23, 2015, 09:02:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4985 views, 1104 downloads, 0 subscriptions

About: CN24 is a complete semantic segmentation framework using fully convolutional networks.

Changes:

Initial Announcement on mloss.org.


Logo Auto encoder Based Data Clustering Toolkit 1.0

by openpr_nlpr - February 10, 2015, 08:30:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4922 views, 913 downloads, 0 subscriptions

About: The auto-encoder based data clustering toolkit provides a quick start of clustering based on deep auto-encoder nets. This toolkit can cluster data in feature space with a deep nonlinear nets.

Changes:

Initial Announcement on mloss.org.


Logo Histogram of Oriented Gradient 1.0

by openpr_nlpr - February 10, 2015, 08:27:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4055 views, 797 downloads, 0 subscriptions

About: This is an exact implementation of Histogram of Oriented Gradient as mentioned in the paper by Dalal.

Changes:

Initial Announcement on mloss.org.


Logo JMLR RL library 3.00.00

by frezza - January 13, 2015, 04:15:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7596 views, 2117 downloads, 0 subscriptions

About: A template based C++ reinforcement learning library

Changes:

Initial Announcement on mloss.org.


Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 9529 views, 2084 downloads, 0 subscriptions

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:
  • Fixed bug where results using same random seed were different with visualization turned on/off
  • Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)
  • Switched from custom logger class to python default
  • Added unit tests
  • Code readability improvements (formatting, variable names/ordering)
  • Restructured TD Learning heirarchy
  • Updated tutorials

Logo PredictionIO 0.7.0

by simonc - April 29, 2014, 20:59:57 CET [ Project Homepage BibTeX Download ] 21155 views, 4655 downloads, 0 subscriptions

About: Open Source Machine Learning Server

Changes:
  • Single machine version for small-to-medium scale deployments
  • Integrated GraphChi (disk-based large-scale graph computation) and algorithms: ALS, CCD++, SGD, CLiMF
  • Improved runtime for training and offline evaluation
  • Bug fixes

See release notes - https://predictionio.atlassian.net/secure/ReleaseNote.jspa?projectId=10000&version=11801


Logo MShadow 1.0

by antinucleon - April 10, 2014, 02:57:54 CET [ Project Homepage BibTeX Download ] 4824 views, 1252 downloads, 0 subscriptions

About: Lightweight CPU/GPU Matrix/Tensor Template Library in C++/CUDA. Support element-wise expression expand in high performance. Code once, run smoothly on both GPU and CPU

Changes:

Initial Announcement on mloss.org.


Logo CXXNET 0.1

by antinucleon - April 10, 2014, 02:47:08 CET [ Project Homepage BibTeX Download ] 5184 views, 1280 downloads, 0 subscriptions

About: CXXNET (spelled as: C plus plus net) is a neural network toolkit build on mshadow(https://github.com/tqchen/mshadow). It is yet another implementation of (convolutional) neural network. It is in C++, with about 1000 lines of network layer implementations, easily configuration via config file, and can get the state of art performance.

Changes:

Initial Announcement on mloss.org.


Showing Items 1-20 of 27 on page 1 of 2: 1 2 Next