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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Caffe is a deep learning framework designed with a focus on expressiveness, efficiency, and modularity, developed by Berkeley AI Research (BAIR) alongside numerous community contributors. The project was initiated by Yangqing Jia during his doctoral studies at UC Berkeley and is available under the BSD 2-Clause license. For those interested, there is an engaging web image classification demo available for viewing! The framework’s expressive architecture promotes innovation and application development. Users can define models and optimizations through configuration files without the need for hard-coded elements. By simply toggling a flag, users can seamlessly switch between CPU and GPU, allowing for training on powerful GPU machines followed by deployment on standard clusters or mobile devices. The extensible nature of Caffe's codebase supports ongoing development and enhancement. In its inaugural year, Caffe was forked by more than 1,000 developers, who contributed numerous significant changes back to the project. Thanks to these community contributions, the framework remains at the forefront of state-of-the-art code and models. Caffe's speed makes it an ideal choice for both research experiments and industrial applications, with the capability to process upwards of 60 million images daily using a single NVIDIA K40 GPU, demonstrating its robustness and efficacy in handling large-scale tasks. This performance ensures that users can rely on Caffe for both experimentation and deployment in various scenarios.

Description

Founded in January 2015, sipXcom emerged from a fork of the sipXecs project, initiated by the eZuce, Inc. development team. The sipXecs and SIPfoundry communities were struggling to expand their developer base due to a limiting contributor agreement, prompting the creation of sipXcom, which features an open contribution model. The source code for sipXcom is licensed under the copyleft-friendly AGLP v3 (Affero General Public License), ensuring greater flexibility for developers. Currently under development, SWARM is the codename for the upcoming iteration of the sipXcom and sipXecs projects, with a production launch expected in early 2017. This new platform will adopt a microservices-based architecture, enhancing scalability, reliability, and configurability beyond what sipX currently offers. SWARM is engineered to be compatible with any computing environment, including dedicated, virtual, or cloud servers, and also allows for hybrid setups that merge on-premise and cloud solutions. With these advancements, sipXcom aims to significantly improve user experience and functionality in the ever-evolving communication landscape.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) Yes 
AWS Elastic Fabric Adapter (EFA) Yes 
AWS Marketplace Yes 
Docker Yes 
Fabric for Deep Learning (FfDL) Yes 
IBM Cloud No 
Lambda Yes 
NVIDIA DIGITS Yes 
OpenVINO Yes 
Polyaxon Yes 
Pop!_OS Yes 
Zebra by Mipsology Yes 

Integrations

Amazon Web Services (AWS) Yes 
AWS Elastic Fabric Adapter (EFA) No 
AWS Marketplace No 
Docker No 
Fabric for Deep Learning (FfDL) No 
IBM Cloud Yes 
Lambda No 
NVIDIA DIGITS No 
OpenVINO No 
Polyaxon No 
Pop!_OS No 
Zebra by Mipsology No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

BAIR

Country

United States

Website

caffe.berkeleyvision.org

Vendor Details

Company Name

sipXcom

Founded

2015

Country

United States

Website

sipxcom.org

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification Yes 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization Yes 

Product Features

PBX

Telephony

Auto-Dialer No 
Call Center Management No 
Call Monitoring No 
Contact Management No 
IVR / Voice Recognition No 
Inbound Reporting No 
Outbound Reporting No 
Predictive Dialer No 
Telemarketing Management No 
VoIP No 
Voice & Data Integration No 

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