KANDULA VENKATA PADMAJA

Driven student ready to translate academic knowledge into practical applications. Possesses strong communication skills and a collaborative approach, enhancing team performance. Eager to learn and contribute effectively to organizational goals.

Sign Language Detection And Telugu Conversion

Developed a real-time sign language detection system using Python and MediaPipe, converting gestures into Telugu text. Addressed cultural nuances and linguistic variations in Telugu sign language data preprocessing. Integrated language translation and text-to-speech for enhanced accessibility among Telugu-speaking communities with hearing impairments. 

Automatic Accident Detection

 Created a robust accident detection system using advanced deep learning techniques, merging 3D CNN, LSTM, and Isolation Forest. Achieved high accuracy with the Car Crash Dataset (CCD) containing 500 accident and 500 non-accident videos. Utilized 3D CNN for extracting spatiotemporal features and LSTM for detecting temporal anomalies. Integrated Isolation Forest for spatial anomaly detection, effectively discerning accidents from normal scenes.

• Participated in the Coders Club College Event and won 2nd Prize in Project Expo for the Sign Language Detection and Telugu Conversion project.