Pinned Repositories
-A-Fine-Windy-Day-HackerEarth
Problem Moving from traditional energy plans powered by fossils fuels to unlimited renewable energy subscriptions allows for instant access to clean energy without heavy investment in infrastructure like solar panels, for example. One clean energy source that has been gaining popularity around the world is wind turbines. Turbines are massive structures that are strategically placed in perpetually windy places to generate the most energy. Wind energy is generated when the power of the atmosphere’s airflow is harnessed to create electricity. Wind turbines do this by capturing the kinetic energy of the wind. Factors such as temperature, wind direction, turbine status, weather, blade length, etc. influence the amount of power generated.
Convolutional-Long-Short-Term-Memory-based-IOT-node-for-Violence-Detection
Abstract— Violence detection has been investigated extensively in the literature. Recently, IOT based violence video surveillance is an intelligent component integrated in security system of smart buildings. Violence video detector is a specific kind of detection models that should be highly accurate to increase the model’s sensitivity and reduce the false alarm rate. This paper proposes a novel architecture of ConvLSTM model that can run on low-cost Internet of Things (IOT) device such as raspberry pi board. The paper utilized convolutional neural networks (CNNs) to learn spatial features from video’s frames that were applied to Long Short- Term Memory (LSTM) for video classification into violence/non-violence classes. A complex dataset including two public datasets: RWF-2000 and RLVS-2000 was used for model training and evaluation. The challenging video content includes crowds and chaos, small object at far distance, low resolution, and transient action. Additionally, the videos were captured in various environments such as street, prison, and schools with several human actions such as playing football, basketball, tennis, swimming and eating. The experimental results show high performance of the proposed violence detection model in terms of average metrics having an accuracy of 73.35 %, recall of 76.90 %, precision of 72.53 %, F1 score of 74.01 %, false negative rate of 23.10 %, false positive rate of 30.20 %, and AUC of 82.0 %.
ctf-tools
Add links to your favorite CTF tools to make other people lives easier .
Data-Structure-Algorithms
Upload Solutions of any coding Platform. In designated folder if not there make new folder and upload.
first-contributions
🚀✨ Help beginners to contribute to open source projects
hacktoberfest
Participate in Hacktoberfest by contributing to any Open Source project on GitHub! Here is a starter project for first time contributors. #hacktoberfest
hacktoberfest-begginer-repo-2022
public repo for Hacktoberfest - 2022 . kindly add the file in appropiate folder or the pull request won't be accepted
hacktoberfest-java
Hacktoberfest contribution repo for Java Devs
Machinehack-Mathcothon-Car-Price-Prediction
With the rise in the variety of cars with differentiated capabilities and features such as model, production year, category, brand, fuel type, engine volume, mileage, cylinders, colour, airbags and many more, we are bringing a car price prediction challenge for all. We all aspire to own a car within budget with the best features available. To solve the price problem we have created a dataset of 19237 for the training dataset and 8245 for the test dataset.
Project-Hub-2022
shreyash2610's Repositories
shreyash2610/Convolutional-Long-Short-Term-Memory-based-IOT-node-for-Violence-Detection
Abstract— Violence detection has been investigated extensively in the literature. Recently, IOT based violence video surveillance is an intelligent component integrated in security system of smart buildings. Violence video detector is a specific kind of detection models that should be highly accurate to increase the model’s sensitivity and reduce the false alarm rate. This paper proposes a novel architecture of ConvLSTM model that can run on low-cost Internet of Things (IOT) device such as raspberry pi board. The paper utilized convolutional neural networks (CNNs) to learn spatial features from video’s frames that were applied to Long Short- Term Memory (LSTM) for video classification into violence/non-violence classes. A complex dataset including two public datasets: RWF-2000 and RLVS-2000 was used for model training and evaluation. The challenging video content includes crowds and chaos, small object at far distance, low resolution, and transient action. Additionally, the videos were captured in various environments such as street, prison, and schools with several human actions such as playing football, basketball, tennis, swimming and eating. The experimental results show high performance of the proposed violence detection model in terms of average metrics having an accuracy of 73.35 %, recall of 76.90 %, precision of 72.53 %, F1 score of 74.01 %, false negative rate of 23.10 %, false positive rate of 30.20 %, and AUC of 82.0 %.
shreyash2610/-A-Fine-Windy-Day-HackerEarth
Problem Moving from traditional energy plans powered by fossils fuels to unlimited renewable energy subscriptions allows for instant access to clean energy without heavy investment in infrastructure like solar panels, for example. One clean energy source that has been gaining popularity around the world is wind turbines. Turbines are massive structures that are strategically placed in perpetually windy places to generate the most energy. Wind energy is generated when the power of the atmosphere’s airflow is harnessed to create electricity. Wind turbines do this by capturing the kinetic energy of the wind. Factors such as temperature, wind direction, turbine status, weather, blade length, etc. influence the amount of power generated.
shreyash2610/ctf-tools
Add links to your favorite CTF tools to make other people lives easier .
shreyash2610/Data-Structure-Algorithms
Upload Solutions of any coding Platform. In designated folder if not there make new folder and upload.
shreyash2610/first-contributions
🚀✨ Help beginners to contribute to open source projects
shreyash2610/hacktoberfest
Participate in Hacktoberfest by contributing to any Open Source project on GitHub! Here is a starter project for first time contributors. #hacktoberfest
shreyash2610/hacktoberfest-begginer-repo-2022
public repo for Hacktoberfest - 2022 . kindly add the file in appropiate folder or the pull request won't be accepted
shreyash2610/hacktoberfest-java
Hacktoberfest contribution repo for Java Devs
shreyash2610/Machinehack-Mathcothon-Car-Price-Prediction
With the rise in the variety of cars with differentiated capabilities and features such as model, production year, category, brand, fuel type, engine volume, mileage, cylinders, colour, airbags and many more, we are bringing a car price prediction challenge for all. We all aspire to own a car within budget with the best features available. To solve the price problem we have created a dataset of 19237 for the training dataset and 8245 for the test dataset.
shreyash2610/Project-Hub-2022
shreyash2610/shreyash
shreYash-G