September 23, 2020 Advanced, Computer Vision, Deep Learning, Python, Technique, Unstructured Data Leave a comment

A Detailed Study of Self Supervised Contrastive Loss and Supervised Contrastive Loss

Introduction Supervised Contrastive Learning paper claims a big deal about supervised learning and cross-entropy loss vs supervised contrastive loss for better image representation and classification tasks. Let’s go in-depth in this paper what is about. Claim actually close to 1% improvement on image net data set¹. Architecture wise, its a very simple network resnet 50 having a 128-dimensional head. If you want you can add a few more layers as well. Architecture and training process from the paper Codeself.encoder = […]

September 22, 2020 ANOMALY DETECTION, Machine Learning Leave a comment

MStream: Fast Streaming Multi-Aspect Group Anomaly Detection

Given a stream of entries in a multi-aspect data setting i.e., entries having multiple dimensions, how can we detect anomalous activities? For example, in the intrusion detection setting, existing work seeks to detect anomalous events or edges in dynamic graph streams, but this does not allow us to take into account additional attributes of each entry… Our work aims to define a streaming multi-aspect data anomaly detection framework, termed MStream, which can detect unusual group anomalies as they occur, in […]

September 22, 2020 INTRUSION DETECTION, Machine Learning Leave a comment

Intrusion Detection for Cyber-Physical Systems using Generative Adversarial Networks in Fog Environment

Cyber-attacks on cyber-physical systems (CPSs) can lead to sensing and actuation misbehavior, severe damages to physical objects, and safety risks. Machine learning algorithms have been proposed for hindering cyber-attacks on CPSs, but the absence of labeled data from novel attacks makes their detection quite challenging… In this context, Generative Adversarial Networks (GANs) are a promising unsupervised approach to detect cyber-attacks by implicitly modeling the system. However, the detection of cyber-attacks on CPSs has strict latency requirements, since the attacks need […]

September 22, 2020 CROSS-LINGUAL TRANSFER, Machine Learning Leave a comment

FarsTail: A Persian Natural Language Inference Dataset

Natural language inference (NLI) is known as one of the central tasks in natural language processing (NLP) which encapsulates many fundamental aspects of language understanding. With the considerable achievements of data-hungry deep learning methods in NLP tasks, a great amount of effort has been devoted to develop more diverse datasets for different languages… In this paper, we present a new dataset for the NLI task in the Persian language, also known as Farsi, which is one of the dominant languages […]

September 22, 2020 Machine Learning, SEMANTIC PARSING Leave a comment

Progressive Semantic-Aware Style Transformation for Blind Face Restoration

Face restoration is important in face image processing, and has been widely studied in recent years. However, previous works often fail to generate plausible high quality (HQ) results for real-world low quality (LQ) face images… In this paper, we propose a new progressive semantic-aware style transformation framework, named PSFR-GAN, for face restoration. Specifically, instead of using an encoder-decoder framework as previous methods, we formulate the restoration of LQ face images as a multi-scale progressive restoration procedure through semantic-aware style transformation. […]

September 22, 2020 Artificial intelligence Leave a comment

Project InnerEye open-source deep learning toolkit: Democratizing medical imaging AI

For over a decade, the Project InnerEye team at Microsoft Research Cambridge has been developing state-of-the-art machine learning methods for the automatic, quantitative analysis of three-dimensional medical images. An important application is to assist clinicians for image preparation and planning tasks for radiotherapy cancer treatment. This task involves a radiation oncologist or specialist technician manually examining and marking up dozens of 3D Computed Tomography (CT) image scans. This may take one or more hours currently, depending on the type of […]

September 22, 2020 Artificial intelligence Leave a comment

In search for future of cloud storage, researchers look to holographic storage solutions

Data storage has always been a key tenet of compute, and with the massive growth in cloud compute, the demand for cloud data storage has opened an avenue for both revisiting prior technologies and developing new ones. It is projected that around 125 zettabytes of data will be generated annually by 2024, and storing this in a cost-effective way is going to be a big challenge. The cloud has also changed the way we think about compute and storage. In […]

September 21, 2020 Python Leave a comment

Python Virtual Environments Explained

What is VirtualEnv? The virtualenv tool creates an isolated Python environment (in the form of a directory) that is completely separate from the system-wide Python environment. What this really means is that any settings, 3rd-party packages, etc. from the system-wide environment do not appear in the virtual environment, so it’s almost like you have a clean Python install. This is useful for when you want to have a clean-slate for your projects. Let’s say you have boto version 2.7.0 installed […]

September 21, 2020 Python Leave a comment

Pyramid Explained

What is Pyramid Pyramid is a Python web framework created from the combination of Pylons and repoze.bfg, resulting in a flexible, easy to use framework. Pyramid puts much of its focus in being flexible, so no application will be constrained by decisions made by the Pyramid creators. For example, you can use Mako or Chameleon for templating, just about any type of database for persistence, and a number of different methods for view routing (the list goes on). Many features […]

September 21, 2020 Python Leave a comment

How to Exploit the Heartbleed Bug

First we explained how it worked, and now, thanks to Jared Stafford (and stbnps on Github for explanations) we can show you how to exploit it. Heartbleed is a simple bug, and therefore a simple bug to exploit. As you’ll see below, it only takes about a single page of Python to exploit this bug. Before we get to the code, here are a few reference links to help you understand the SSL protocol: The Code #!/usr/bin/python # Quick and […]

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