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anomaly-detection-using-spatiotemporal-autoencoder

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Better dates & times for Python

avoid-try-except-repetition

Avoid writing multiple try-except blocks to make make code more readable

class-activation-map

classification-image-segmentation-and-sentimental-analysis

A deep learning model using tensor flow which classifies pre-described images in a photo when given as input. I have implemented this as a part of my course Unstructured Data Analytics at Carnegie Mellon University. Please use requirements.txt to install required softwares and proceed for the code. Data can be found in the zip files below. Contact me for more details.

cpp-tutorials

Under construction

deep-learning-photo-ocr

deepwilson.github.io

Personal blog

detr

fundamentals of DETR

dlcv

Concepts and implementations related to deep learning for computer vision

dsa-practice-codes-python-c-

five-video-classification-methods

Code that accompanies my blog post outlining five video classification methods in Keras and TensorFlow

insights

jpeg-artifacts-removal-using-dncnn

Using a Denoising CNN to remove JPEG artifacts arising from compressing images

keras-cv

Industry-strength Computer Vision workflows with Keras

latex-ocr

pix2tex: Using a ViT to convert images of equations into LaTeX code.

librealsense

Intel® RealSense™ SDK

mdetr

neuralnetwork-xor

A simple python neural network implementation for the XOR problem

realsense2sample

RealSense SDK 2 Sample Program

sketch_guided_detr

ssd-tf2

A super clean implementation of SSD (Single Shot MultiBox Detector) made possible by Tensorflow 2.0

thesis_sketch_guided_detr

Academic project page for Master's Thesis

universal-data-augmentation-for-bounding-boxes

Avoid writing separate code for bounding box updation for each type of data augmentation for Object Detection pipelines. Optimized for integration with tf.data pipeline for GPU execution.

vehicle_reid