Method for analyzing sensor data, executed by an analyzing device comprising a processor, a first memory and a second memory, wherein the processor is capable of executing multiple threads in parallel based on instructions and/or data stored in the first memory, wherein the second memory stores a plurality of neural networks, a neural network specifying successive layers, wherein at least one of said neural networks is a convolution neural network comprising convolution layers followed by fully-connected layers, the method comprising determining analysis results by processing the sensor data with the neural networks, wherein processing the sensor data with the neural networks comprises, for the at least one of said neural networks: - classifying (S1-S4) the layers of the at least one of said neural networks into a first set of layers and a second set of layers, wherein the second set of layers follows the first set of layers, wherein said first set includes said convolution layers and said second set includes said fully-connected layers, - executing (T2, T3) in parallel, by the processor: - a first thread which comprises loading said first set of layers in the first memory and executing said first set of layers, and - a second thread which comprises loading said second set of layers in the first memory, - after finishing execution of the first thread, executing the second set of layers. wherein the second memory stores a plurality of neural networks, a neural network specifying successive layers, wherein at least one of said neural networks is a convolution neural network comprising convolution layers followed by fully-connected layers, the method comprising determining analysis results by processing the sensor data with the neural networks, wherein processing the sensor data with the neural networks comprises, for the at least one of said neural networks: - classifying (S1-S4) the layers of the at least one of said neural networks into a first set of layers and a second set of layers, wherein the second set of layers follows the first set of layers, wherein said first set includes said convolution layers and said second set includes said fully-connected layers, - executing (T2, T3) in parallel, by the processor: - a first thread which comprises loading said first set of layers in the first memory and executing said first set of layers, and - a second thread which comprises loading said second set of layers in the first memory, - after finishing execution of the first thread, executing the second set of layers. - classifying (S1-S4) the layers of the at least one of said neural networks into a first set of layers and a second set of layers, wherein the second set of layers follows the first set of layers, wherein said first set includes said convolution layers and said second set includes said fully-connected layers, - executing (T2, T3) in parallel, by the processor: - a first thread which comprises loading said first set of layers in the first memory and executing said first set of layers, and - a second thread which comprises loading said second set of layers in the first memory, - a first thread which comprises loading said first set of layers in the first memory and executing said first set of layers, and - a second thread which comprises loading said second set of layers in the first memory, - after finishing execution of the first thread, executing the second set of layers.