IndoLLNet v1.0

The 2021 Javanese Script Congress proposed replacing Latin script with Javanese script in public life across Yogyakarta. However, this faces significant challenges due to the lack of widespread literacy in Javanese, especially among younger generations.

IndoLLNet introduces a CNN-based framework for handwritten character recognition covering Javanese, Sundanese, and Lampung scripts — handling diacritics (sandhangan), conjuncts (pasangan), numerals, and all six vowel sounds.

# Dimensions of input and kernel
input_h, input_w = len(input_matrix), len(input_matrix[0])
kernel_h, kernel_w = len(kernel), len(kernel[0])

# Output size
output_h = input_h − kernel_h + 1
output_w = input_w − kernel_w + 1

# Convolution loop
for i in range(output_h):
    for j in range(output_w):
        conv_sum = 0
        for ki in range(kernel_h):
            for kj in range(kernel_w):
                conv_sum += input_matrix[i+ki][j+kj] \
                            * kernel[ki][kj]
        output_matrix[i][j] = conv_sum

# ReLU + bias
bias = random.choice([−1, 1])
relu_map = [[max(0, v+bias) for v in row]
            for row in output_matrix]

# Max pooling 2×2, stride 2
pooled_map[i//2][j//2] = max(pooling_region)

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